class_docstr: Test class for tf & pytorch make_optimizer functions.
docstr: Test make_optimizer function with tuple as first argument.
docstr_tok: ["Test","make_optimizer","function","with","tuple","as","first","argument","."]
code: def test_torch_make_optimizer_with_tuple(self):
      """Test make_optimizer function with tuple as first argument."""
      optimizer_type = (torch.optim.Adam, {"lr": 0.1})
      module = torch.nn.Linear(2, 1)
      optimizer = make_optimizer(optimizer_type, module=module)
      # pylint: disable=isinstance-second-argument-not-valid-type
      assert isinstance(optimizer, optimizer_type)
      assert optimizer.defaults["lr"] == optimizer_type[1]["lr"]
  
imports: import csv
  import math
  import tempfile
  import akro
  import dowel
  from dowel import logger, tabular
  import numpy
  import pytest
  import tensorflow
  import torch
  from garage import _Default, EnvSpec, EpisodeBatch, log_multitask_performance, log_performance, make_optimizer, rollout, StepType
  from garage.envs import GymEnv
  from tests.fixtures import TfGraphTestCase
  from tests.fixtures.envs.dummy import DummyBoxEnv
  from tests.fixtures.policies import DummyPolicy
label_desc: Use image node_id 5 for calling the TestOptimizerInterface obj's underlying member method code with example usage: obj.test_torch_make_optimizer_with_tuple() without return types